Landlord's equal cards force generation algorithm

In recent years, deep learning has developed rapidly and gradually infiltrated into various fields. As a rookie, generation‐based confrontation networks based on deep learning show excellent characteristics in many aspects. This study presents two innovative ideas, the same card force and generation cards algorithm. The generation of the equivalent cards force based on the generation of confrontation networks is studied. For the same period of time in the regular game, players will be issued different types of cards with similar card force, so as to distinguish the player level, the theory of the equal force is proposed. Based on the average and variance of scores obtained after the completion of a game, the cards are divided into ten different types of cards. On this basis, the use of generating a counterfeit network Generative Adversarial Nets generates a large number of cards of the equal card force. In the actual game, a network model is generated to generate a large number of game cards with the same force and distributed to different table numbers, so that the points scored by the landlords in different matches can have the characteristics of mutual appraisal.